Intelligent localized high-resolution imaging of tubulars

ABSTRACT

A device and method used to image wells and other fluid-carrying tubulars having localized features of interest. The device scans large areas of the tubular first in a low-resolution mode using an ultrasound sensor and in a high-resolution mode using a camera, then identifies areas that contain those localized features with some probability. The device images are stored for further image processing. The two sensors are axially spaced-apart on the device. A computer remote from the imaging device renders a visualization of the tubular and localized features using the optical and ultrasound images.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.17/035,887, filed Sep. 29, 2020, which claims priority to claimspriority to GB Application No. GB1914258.7, filed on Oct. 3, 2019, thedisclosure of each of which is incorporated herein by reference in itsentirety.

FIELD OF THE INVENTION

The invention relates generally to inspection of fluid-carryingconduits, in particular, acoustic sensors in oil & gas wells, waterwells, geothermal wells, water mains or pipelines.

BACKGROUND OF THE INVENTION

In tubulars there often arises a need to inspect the structure forintegrity. For example, hydrocarbons in production casing maycontaminate ground water if there are cracks or deformations in thecasing. Similarly, water resources may be lost to leaks in water mains.Ultrasound sensors and cameras located with an imaging device are knownways of imaging such structures to detect problems thus protecting theenvironment.

As these tubulars may be several kilometers long, the logging speed ofthe tool becomes an issue. To obtain high resolution images, the imagingtool captures a frame every millimeter, with as many scan lines aspossible. However, at practical memory limits, frame rates andprocessing speeds, it becomes very difficult to log tubulars that aremany kilometers long.

Existing ultrasound tools comprise an array of piezoelectric elementsdistributed radially around the tool housing. The top surface of eachelement faces radially away from the tool towards the wall of thetubular. The reflected waves are received by the same elements and thepulse-echo time of the waves are used to deduce the distances to theinner and outer walls and voids therebetween. The elements may be angledaway from a normal sonification at the surface, such that some of theenergy reflects away from the sensor and some backscatters off features,per PCT Application WO 2016/201583 published Dec. 22, 2016 to DarkvisionTechnologies.

In some logging operations, the whole tubular need not be imaged, butonly certain areas where a localized feature of interest exists. As usedherein, localized features may be perforations, connections, wash-outs,fiber cable clamps (i.e. features that do not extend over the entirewell or pipe. However, currently such operations require that a largelength of the tubular be imaged in high-resolution and stored forsubsequent visualization at the surface. This limits the logging speedof tools to a few meters per minute.

SUMMARY OF THE INVENTION

To address the shortcomings of the current tools, a new downhole tooland method are provided that separate the operation into scanning forcandidate localized features and then imaging them. The scanning uses alow-resolution mode to generate first images that are then processed inreal-time using a processor to detect candidate features. The imaging ofthe candidate area uses a high-resolution mode. The high-resolutionimages may be processed offline or also in real-time.

In accordance with a first aspect of the invention there is provided amethod of imaging localized features in a tubular, comprising: deployingand continuously logging an imaging device longitudinally through thetubular, which imaging device comprises a) a phased array ultrasoundsensor and b) a camera, longitudinally spaced-apart from the ultrasoundsensor, and having a higher density of sensor elements than theultrasound sensor; imaging the tubular with the camera to generateoptical images; imaging the tubular with the phased array ultrasoundsensor to generate ultrasound images; wherein both optical images andultrasound images capture localized features in the tubular; andprocessing the optical and ultrasound images to visualize the tubularand localized features to a user.

In accordance with a second aspect of the invention there is provided asystem for imaging localized features in a tubular in an oilwellincluding: an elongate imaging device deployable in and moveable throughthe tubular; a phased array ultrasound sensor of the imaging device; acamera of the imaging device, longitudinally spaced-apart from thephased array ultrasound sensor and having higher density of sensorelements than the ultrasound sensor; one or more memory units forstoring sensor data. There is a processor arranged to: operate thecamera to image the tubular to generate optical images; operate thephased array ultrasound sensor to image the tubular to generateultrasound images; and store images of the images in the memory. Whereinboth optical images and ultrasound images capture localized features inthe tubular. The system includes a computer remote from the imagingdevice and arranged to process the optical and ultrasound images tovisualize the tubular and localized features to a user.

In accordance with a third aspect of the invention there is provided amethod of imaging localized features in a tubulars, comprising:deploying and continuously logging an ultrasound imaging devicelongitudinally through the tubular; scanning the tubular with a firstsensor of the device to generate first data; automatically identifyingcandidate localized features of the tubular using the first data;defining areas surrounding candidate localized features; and imaging thedefined areas using a second sensor, longitudinally spaced-apart fromthe first sensor, to generate second data.

In accordance with a fourth aspect of the invention there is provided adevice for imaging localized features of a tubular comprising: anelongate body deployable in and moveable thru the tubular; a firstsensor and second sensor, longitudinally spaced-apart from each other;one or more memory units for storing sensor data; and a processorarranged to: operate the first sensor to scan the tubular for localizedfeatures; operate the second sensor to image the localized features; andstore images of the localized features in the memory.

The step of imaging captures data may be at a higher resolution than thestep of scanning.

The higher resolution may be due to higher density of elements in thesecond sensor compared to the first sensor. The higher resolution may bedue to a higher frame rate used for the second sensor compared to thefirst sensor.

The localized features may be at least one of: perforations, ports,holes, corrosion pits, cracks, connections, wash-outs, or cable clamps.

Identifying candidate localized features may include comparing firstdata to first sensor characteristics that define a selected featuretype.

The first sensor or second sensor may include an electromagnetic sensorarray. The first sensor or second sensor may include an ultrasonicsensor array, preferably arranged as a phased-array. The first sensor orsecond sensor may be an optical array. The first sensor or second sensormay be a radial array of sensor elements. The second sensor may includea radial-facing sensor rotated about a longitudinal axis of the devicethrough a sector angle containing each defined area.

Setting imaging parameters of the second sensor may be based on a typeof the localized feature.

The method may image process the second data to create a geometric modelof the tubular and the localized features. The steps of scanning andimaging capture a surface of a casing in the tubular.

The one or more memory units stores second sensor parameters based on atype of the localized feature.

The one or more memory units further stores instruction operable by theprocessor to: identify candidate localized features of the tubular usingfirst data generated by the first sensor; define areas surroundingcandidate localized features; and directing the second sensor to imageat the defined areas to generate second data.

The one or more memory units stores a features database that defines aplurality of feature types by signal characteristics for the firstsensor.

The second sensor comprises a radial-facing sensor rotated about alongitudinal axis of the device through a sector angle containing eachdefined area.

Thus preferred embodiments of the invention enable the device to imagelocalized features in high-resolution while continuously logging thetubular at high speed.

BRIEF DESCRIPTION OF THE DRAWINGS

Various objects, features and advantages of the invention will beapparent from the following description of embodiments of the invention,as illustrated in the accompanying drawings. The drawings are notnecessarily to scale, emphasis instead being placed upon illustratingthe principles of various embodiments of the invention.

FIG. 1 is a cross-sectional view of an imaging device deployed in atubular in accordance with one embodiment of the invention.

FIG. 2 is a cross-sectional view of an imaging device in a well.

FIG. 3A is a perspective-view of a radial acoustic array and its imagingfield.

FIG. 3B is a perspective-view of a radial acoustic array in a conicalarrangement.

FIG. 4 is a block diagram for compressing ultrasound data.

FIG. 5 is a circuit block diagram for driving ultrasound sensors.

FIG. 6 is a signal flow diagram for processing data in scanning andimaging modes.

FIG. 7 is a flowchart for scanning and imaging localized features.

FIG. 8 is a side view of an imaging device with two radial arrays.

FIG. 9 is a side view of an imaging device on an end effector.

FIG. 10A is an illustration of reflections off micro features in a highangle of incidence embodiment;

FIG. 10B is a graph of reflection timings from the embodiment in FIG.9A.

FIG. 11 is an unwrapped low-resolution scan of a cylindrical pipe withlocalized features.

FIG. 12 is a high-resolution scan of a localized features.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

With reference to the accompanying figures, devices and methods aredisclosed for capturing, processing, and storing images from tubular,particularly localized features of the tubular. The tubular may carryhydrocarbons or water and has an elongate, cylindrical form factorthrough which the device can move longitudinally. The device typicallyalso has an elongate form factor and is sized to be deployable withinthe well or pipe. Wells include cased and uncased wells, at any stagefrom during drilling to completion to production to abandonment.

An object of the present invention is to image certain localizedfeatures, such as perforations, small localized areas of corrosion andclamps. As used herein, localized features are only located in a smallunknown area, and do not extend over the whole tubular. Thus they can beimaged by a sub-field of the full imaging field of the sensor. Localizedfeatures should also be sufficiently distinct that they can beidentified by automated techniques. Thus small patches (10-100 mm²) ofheavily pitted pipe would be a localized feature to target, whereasgeneral corrosion of the surface would be a continuous feature imagedusing existing full-field techniques.

As a persistent example used hereinbelow, the localized feature may be aperforation thru a production casing of an oil well. Perforations aretypically 7-12 mm in diameter and spaced apart in a production sectionof the tubular. The (lack of) reflections at the middle of a perforationand glints from the edges make such a feature detectable using automatedtechniques.

In accordance with one embodiment of the invention, there is provided animaging device 10 for imaging a tubular 2, as illustrated in FIGS. 1 and2 . The imaging device 10 generally comprises a first sensor 11, asecond sensor 12, a body 16, a processor 14, and one or morecentralizing elements 20. In use, the first sensor is upstream and thesecond sensor is downstream with respect to the logging direction, suchthat localized features reach the first sensor before the second sensor.

The first sensor provides a low-resolution scanning of the wholecross-section of the tubular in an initial pass, and the second sensorprovides a high-resolution imaging of the localized area of interest ina subsequent, slightly later, pass. The sensors are separated by somedistance D in the axial direction of the device to provide some transittime during which the processor identifies candidate areas for imagingby sensor 12.

The First Sensor is preferably an optical array or an acoustic array asdescribed below, however, given the lowered precision initially needed,it may be another sensor type such as an electromagnetic sensor (e.g.eddy current sensor, magnetic flux sensor), micro-caliper, ormicro-radar sensor. The first and second sensors may have similarresolutions, such that the processor uses the second image to combinewith or confirm localized features detected in the first image. Howeverin preferred embodiment, the First Sensor has lower sensor density, usessimpler electronics, and/or processes less signals in order to identifyan area of the tubular having a localized feature with some probability.For example, a micro-caliper array having just 10 arms could detect aperforation within a sector of 36° with simple signal processing.

However, a first sensor based on an acoustic array or camera providesmore flexibility in the types of features to target, with increaseddetection confidence but at the cost of more complexity.

Preferably the second sensor is a high-resolution camera or an array ofacoustic sensor elements, more preferably arranged as a phased array.Preferably, compared to the first sensor, the second array has highersensor density with processing circuits that support higher resolutionimaging. The relative resolution and design options are discussed below.

In one embodiment, the first sensor is an optical or ultrasonic sensorand the second is a magnetic sensor. This arrangement providesconfirmation sensor data at a candidate location.

The axial resolution depends on the logging speed and frame rate. Forexample, for a device moving axially at 15 m/s, in low-resolution modeof a frame rate of 60 fps the axial resolution will be 4.2 mm. Inhigh-resolution imaging mode of 200 fps, the axial resolution will be1.25 mm.

Optical Sensors

A line camera or the more common matrix camera may be used to scan andimage the tubular. The Second Sensor may be characterized by one or moreof: a high pixel-count array; electronics supporting a high frame rate(100 fps+); higher pixel depth (12-bit+), and RGB channels. Conversely,the First Sensor could have lower pixel count, lower frame rate, lowerpixel depth and monochrome elements.

Downhole cameras similar to those used in wells currently may besuitably modified to provide the First or Second Sensors. For example,US20160259237A1 “Side view downhole camera and lighting apparatus andmethod” filed 19 Nov. 2014 describes a side-view camera that is rotatedwith a motor to capture 360° around the casing. Alternatively the camerasystem may comprise four radial-facing cameras, each capturing slightlyoverlapping sectors of the well to capture a 360° image, after stitchingsectors together.

Similar to alternative ultrasound embodiments described hereinbelow, anoptical sensor may be use in: a rotating head embodiment; two sensors ofsimilar specifications providing redundant imaging; or a single sensorarray that is axially displaceable.

Acoustic Sensor Arrays

An acoustic sensor array comprises a plurality of acoustic sensorelements, preferably operating in the ultrasound band, preferablyarranged as an evenly spaced one-dimensional radial array (see FIGS. 3A,3B). The frequency of the ultrasound waves generated by the sensor(s) isgenerally in the range of 200 kHz to 30 MHz, and may be dependent uponseveral factors, including the fluid types and velocities in the well orpipe and the speed at which the imaging device is moving. In most uses,the wave frequency is 1 to 10 MHz, which provides reflection frommicron-sized point scatterers. The sensors may be piezoelectric, such asthe ceramic material, PZT (lead zirconate titanate). Such sensors andtheir operation are well known and commonly available. Circuits 14 todrive and capture these arrays are also commonly available.

The number of individual elements in the sensor array affects theazimuthal resolution of the generated images. Typically, each sensorarray is made up of 32 to 2048 elements and preferably 128 to 1024elements. The logging speed and frame rate determines the axialresolution. Multiple sensor elements, per aperture 15, operate in aphase delayed mode to generate a scan line 13. There may be as many scanlines as elements by changing the aperture by a single element for eachscan line.

The sensor elements may be distributed radially, equidistant around thebody of the device. As seen in FIG. 3A, the sensor elements 13 may besubstantially outward, radially-facing. A first reflection is receivedfrom the inner wall and then a second reflection is received from theouter wall. However, there may be multiple reflections as the wavebounces between walls. A receive window Rx is pre-set by the operator ordevice for when the processing circuit 14 should start and end recordingof reflected waves. For example, in the case of a large diameter, thickcasing in fluid with a slow speed of sound, the device can startrecording later and for longer.

This sensor arrangement captures a ring-shaped cross-sectional slice(from 27 to 28) of the tubular covering up to 360° around the array 12.As the device is moved axially in the tubular the ring-shaped sensorcaptures slices of the tubular that are perpendicular to thelongitudinal axis of the well. Plural slices are combined to detect orimage the localized object.

In the alternative arrangement of FIG. 3B, the sensor elements aredistributed on a frustoconical surface with elements facing partially inthe longitudinal direction of the device, (and thus in the longitudinaldirection when in the well). Thus, the radial sensors are angled upholeor downhole to form an oblique-shaped conical field of view. The conemay have a cone angle β of 10-45°, preferably about 20′. In thisarrangement, much of the sound wave reflects further downward, but asmall portion backscatters off features in the wall back towards thesensor. FIG. 3B shows acoustic pulses (moving in the direction of thedashed lines) transmitted towards inner wall, most of which bouncesdownward and some backwards to the sensor 11. Some of the wave energy(dot-dashed lines) propagates to the outer wall, then partially back tothe sensor.

This conical design may also face uphole, i.e. towards the proximal endof the device and the operator. Either of the sensors 11, 12 may belocated at an end of the device (e.g. FIGS. 3A, 3B) or between the ends(e.g. FIG. 2 ).

Scan Frame

An acoustic sensor element can both transmit and receive sound waves, ina pulse-echo arrangement. A plurality of sensor elements cooperates as aphased-array to generate a steered and focused wavefront. In FIG. 3A,scan line 13 (dashed line) appears to radiate out from the center of thefour sensors in aperture 15 (enveloped by the dotted line). The numberof scan lines N that make up a full frame may be the same as the numberof elements M in the array, but they are not necessarily the same.

The timing of each scan comprises a transmission window Tx, receivingwindow Rx and dwell period therebetween. As used herein, a scan line 13is the stream of data received during Rx and may be converted tophysical coordinates using the speed of sound thru the fluid.

By way of example, the transmission step may include selecting theelements in the aperture, calculating beamforming timings, loading thepulse timings from the FPGA 84, activating the pulser 81 and MUXes 82 topulse all elements. The dwell period may be set by the operator based onthe expected diameter of the pipe and speed of sound in the well fluid.The Rx window may be set to capture the first reflected pulse from theinner radius of interest (27) until the last element has received thelast pulse that could reflect off the outer radius of interest 28 (SeeFIGS. 2A and 7 ). The scan line's capture radii 27/28 will normally bewider than the actual wall thickness.

As discussed above, the aperture 15 is a set of neighboring sensorelements that individually contribute towards the constructive wavefrontand increase its acoustic energy. There may, for example, be 32 or 64elements in the aperture that are selected from the whole array bymultiplexors. Normally these are a symmetrical set of elements oppositethe pipe spot to be sonified, i.e. the sonified spot and aperture centrehave the same azimuthal angle θ, relative to the center of the device.

FIG. 5 shows an example circuit 80 dedicated to transmitting, receivingand processing ultrasound waves. These circuits are common in ultrasoundimaging and the skilled person is assumed to be familiar with chips,such as LM96511 from Texas Instruments. The raw, digital output of FIG.5 is written to non-volatile Data Memory 36, shown in FIG. 4 .

From the above discussion on sensor arrays, a number of differentparameters are clearly selectable for optimizing the scanning andimagine modes. Examples of parameter selections are provided in theembodiments that follow.

Double Radial Array

A preferred embodiments is shown in FIG. 7 , whereby a First SensorRadial Array 11 is axially separated from Second Sensor Radial Array 12.As shown, the first sensor has fewer sensing elements (or is less dense)but scans radially all around the device. Conversely the second sensorhas densely arranged elements but only images sector 26.

Compared to the Second Sensor Array, the First Sensor Array usesparameters that optimize for lower-resolution and lower data rate. TheFirst Sensor Array's may be designed with one or more of the following:a) a lower density of sensor elements, e.g. ≤128 elements or ≤256elements; b) lower frame rate, e.g. ≤25 fps or ≤50 fps; c) fewerelements in the aperture, e.g. ≤16 elements; d) no beamforming; e) lowerfrequency, e.g. ≤1 MHz.

Rotating Head Imaging Array

In certain embodiments, the second sensor is physically rotatablerelative to the housing of the device. This is sometimes called a‘spinning head’. This second sensor may comprise one or more sensorelements that rotate to a starting angle then rotate while imaging to anend angle, thus sweeping the candidate area. In the case of a singleelement, the second sensor may be quickly swept back and forth severaltimes at high frame rate to capture the area in both high azimuthal andhigh axial resolution.

The second sensor may use the sensor disclosed by patent applicationGB1813356.1 entitled “Device and Method to Position an End Effector in aWell” to Darkvision Technologies Inc, incorporated herein by reference.As disclosed therein and shown in FIG. 8 end-effector 46 is rotatable(motion Θ about axis Z) and laterally translatable in transverse planeY, X. In this case array 12 comprises sensor elements distributed in thelongitudinal axis of the device, such that sweeping the array about Z ortranslating sideways (i.e. perpendicular to the array) captures a 2Dimage of the surface of the tubular.

To capture a high-resolution image, the second sensor sweeps across thesector of the candidate area fast enough, relative to the logging speed,to achieve the desired azimuthal resolution.

Axially Displaced Single Array

In an alternative embodiment, a single radial sensor array is used toperform both the low-resolution scanning mode and high-resolutionimaging mode. The array is located on an axial displacement portion,connected to an actuator. The actuator displaces the array in adirection opposite to the logging direction and at a higher speed thanthe logging speed. Thus the single array gets at least two passes at thesame features: the first time scanning for candidate localized features;the second time imaging just the localized candidate area; wherein theprocessor identifies localized features and proposes candidate areas forimaging.

The array be located on a first device that is coupled to a strokerdevice. The first device may hold the electronics for operating thesensor and processing/storing ultrasound images. The stroker may be aversion of those know in the art, adapted to counter the speed andmovement resolution needed to counter the logging movement. The strokercomprises an actuator (e.g. hydraulic cylinder) for displacing the firstdevice. Compared to certain strokers, the present stroker is designedfor speed, rather than pushing strength.

The array may be connected to and axially displaced by an actuatorwithin the body of the imaging device. One such device is disclosed bypatent application GB1813356.1 entitled “Device and Method to Positionan End Effector in a Well” to Darkvision Technologies Inc. As shown inFIG. 8 , sensor array 12 is located on an end effector 46 and axiallydisplaced by distance D by a rod or screw 41 connected to actuators,such as stepper motors.

The length of the stroke, like the separation distance D of FIG. 8 ,provides time for the processor to identify candidate features and setup the sensor to operate in high-resolution mode. For example, the MUXchannels and the FPGA phase delays are set for the aperture in thesector of the array opposite the localized area to image.

Indeed, the array may get more than two captures or a continuous captureof a localized area by re-displacing the array or speed matching thelogging speed.

Surface Imaging Using Time of Flight

Patent application GB1901669.0 filed 6 Feb. 2019 entitled “AcousticSurface Imaging Using Time of Flight,” incorporated herein in itsentirety, discloses how to capture surface data of a well or pipe bysetting the sensor to sonify the surface at a high angle of incidence.This defocused wave captures an axially enlarged area and separatesreflections from point scatterers within that area by their time offlight t₁-t₅ (see FIGS. 9A and 9B). That is, reflections that returnlater come from further points along the surface, whereby the distancesare convertible from knowing the speed of sound in the fluid.

This sensor arrangement may be used for the various scanning and imagingsteps described above, including use the first and/or second sensorarray or in the axially displaceable single sensor array embodimentabove. As in the above embodiments, the resolution may be increased byusing more sensor elements, higher frame rate, and adjusting sensorsettings. In this sensor arrangement, imaging may also be improved byincreasing the oversampling, i.e. the amount of overlapping area inconsecutive frames, which overlapping is useful in image processing toremove noise and reinforce true surface scatters. This approach alsoprovides good registration as the point reflectors move from frame toframe from which the processor can measure the logging speed.

For example, in low-resolution scanning, consecutive frames may overlapvery little or not at all. A localized feature type may simply bedefined by two or more strong reflections separated by a certaintime/distance. This makes real-time identification possible. Conversely,for high-resolution imaging there may be 60-80% area overlap onconsecutive frames, capturing the same points 3-5 times. The imageprocessing becomes more complex here, as the processor performsautocorrelation of multiple frames to remove noise, enhance realfeatures and correct for changes in incidence angle.

Selection of Feature Type

In order to quickly identify candidate features and candidate areas andreduce the number of areas to image in high resolution, it is preferableto select the feature type of interest before the logging operation.Each feature type is associated with machine readable definitions andassumptions, such as form factor, shape, size, spacing between features,surface texture. Each feature type may be defined by pluralcharacteristics for the first sensor. Such definitions may specify theexpected size, aspect ratio, and signal strength that the first sensorwould return if the first data set contained that feature type. Forexample, a ‘perforation’ feature type may be defined by an azimuthallyrotatable set of signal ranges for each of N acoustic elements in thefirst array, over S frames, including a contiguous region having weakreflections where the perforation is located.

Detection Algorithms

Once the feature type is selected, the definitions of the expectedfeature type are loaded into cache on the device processor 14 andcontinually compared in real-time to incoming data from the firstsensor. The processor may use detection algorithms to determine matchingvalues greater than a threshold value to identify candidate areas thatcontain that feature type with some probability. By determining theazimuth and depth (Θ, Z) where the match is strongest, the processoridentifies candidate locations (Θ, Z) that needs to be further imagedusing the second sensor.

As seen in FIG. 11 , candidate area 9 can be defined by bounding box,centered at the identified location and as wide (ΔΘ) and tall (ΔZ) asthe localized feature. The candidate area could also be defined as acircle or oval centered at the candidate location with diameter similaror larger than the feature size. In order for the second image to be ofsignificantly higher resolution, it is preferable to keep the candidatearea as small as possible, e.g. just larger than the expected orobserved feature's size.

FIG. 7 is a low-resolution 2-D ultrasound image that has captured threeperforations, which were then auto identified and bounded by areas 9.

The detection algorithm may be one or more of: autocorrelation, circlefind, Convolutional Neural Net, Region Proposal, Template matching,computer vision properties of candidate features. Such algorithms areknown to the skilled person and may be modified to work with a givenFirst Sensor data.

To simplify the processing for identifying localized features in thefirst sensor data set, the data may be pre-processed or less data may beused compared to the second data set. For example, for the first dataset, the processor may use only the first reflection, only the strongestreflection or only reflections within a limited receive window.

Each candidate area may be converted to units native to the secondsensor, e.g. sector angle, number of scan lines, aperture size, framerate, and start time given the separation distance D. The Second Sensormay then be coordinated by physically moving the sensor or electricallyactivating the appropriate elements to image each candidate area. Eachfeature type may also be associated with parameters for optimizing thesecond sensor for imaging them. For example, lower resolution parametersmay adequately image large feature types or angled beam forming mayoptimally capture the edges of cable clamps.

This second sensor captures a high-resolution image and stores it innon-volatile device memory 36 or sends it to an Operations Computer 18.The image may be processed on the device or on a remote computer 19either in real-time or after logging. The memory required for the set ofsecond sensor images is much less than imaging the entire tubular andenables the image processing to focus only on these smaller areas.

Registration

In order for the high-resolution imaging pass to image the candidatearea 9 accurately, the logging speed should be steady and known. Thedevice may comprise sensor(s) and processing to observe the axiallogging speed of the device through the tubular. From this loggingspeed, the device's processor determines when to start the imaging.Given the inherent uncertainty in the instantaneous logging speed, thecandidate area 9 is set sufficiently axially longer than the size of thelocalized feature that has been identified.

For example, sensors in wheels contacting the tubular surface maydirectly measure the speed of the device relative to this tubular.Alternatively, the device processor 14 may determine the logging speedby processing the images from the First or Second Sensor to register thescanned features of the tubular and calculate the axial movement ofthese features from between frames or from first sensor to secondsensor. Any one of the sensors can also be used for registration bydetecting micro features provided they have sufficient axial resolutionand sufficiently large axial field of view to capture multipledistinguishable micro features. The processor can then useautocorrelation or image processing to determine the rate of movement ofmicro features through the field of view. Micro features can be scale,pitting or corrosion that return a reflection ‘fingerprint’.

Deployment System

The imaging device includes a connection to a deployment system forrunning the imaging device 10 into the well 2 and removing the devicefrom the well. Generally, the deployment system is wireline 17 or coiledtubing that may be specifically adapted for these operations. Otherdeployment systems can also be used, including downhole tractors andservice rigs. The axial moving (i.e. logging) is preferable continuousand at a constant speed.

The deployment system may lower the device downhole to a toe of the wellthen back uphole towards the surface. In preferred operations, scanningand imaging occur during the uphole movement, when the deployment systemis typically most smooth. The downhole movement can be much faster toreduce overall job time. Optionally, the device may scan the tubularduring the downhole movement to survey the tubular at a high level,which survey data may be processed to estimate sections of the tubularlikely to have the features of interest.

Without loss of generality, each of these components may comprisemultiples of such chips, e.g. the memory may be multiple memory chips.For the sake of computing efficiency, several of the functions andoperations described separately above may actually by combined andintegrated within a chip. Conversely certain functions described abovemay be provided by multiple chips, operating in parallel. For example,the LM96511 chip operates eight sensors, so four LM96511 chips are usedto operate an aperture of 32 sensors.

It will be appreciated that data processing may be performed with pluralprocessors: on the device, at the operations site, and optionally on aremote computer. The term ‘processor’ is intended to include computerprocessors, cloud processors, microcontrollers, firmware, GPUs, FPGAs,and electrical circuits that manipulate analogue or digital signals.While it can be convenient to process data as described herein, usingsoftware on a general computer, many of the steps could be implementedwith purpose-built circuits. In preferred embodiments of the presentsystem, the device processing circuit 15 provides signal conditioning,data processing to identify candidate feature in the low-resolution scanand high-resolution data storage. The remote processor may then performimage processing on the high-resolution images and 2D/3D rendering forvisualization of any features found.

It will be appreciated that the various memories discussed may beimplemented as one or more memory units. Non-volatile memory is used tostore the compressed data and instructions so that the device canfunction without continuous power. Volatile memory (RAM and cache) maybe used to temporarily hold raw data and intermediate computations.

Rendering

Computer 18 or 19 at the surface may render a 2D or 3D geometric modelto visualize the tubular to the user. A geometric model represents thesurface features spatially (in radial and depth coordinates) and may bestored or displayed in their native polar form or unrolled as a flatsurface.

In the present system, some localized features of the tubular are imagedin high resolution and some parts in low resolution, which may or maynot be stored. The imaged features may be further image processed tofilter the signals, smooth surfaces, and extract properties (e.g.diameter, size, depth, fluid flow, surface characteristics)

A rendering module running on that computer stitches together the imagesand processes localized features with low-resolution images of the restof the tubular, if they exist. The data from the first sensor will haveless radial, depth and azimuthal resolution than data from the secondsensor. The rendering module may use the overlapping high- andlow-resolution images at the same locations to better register andfilter the low-resolution images, i.e. to modify the first sensor datasuch that it conforms with the nearby second sensor images.

Without the low-resolution image stored and copied to the surface, therendering module may simulate the tubular data using expected propertiesof the tubular and/or properties from the high-resolution localizedfeatures. For example, the operator may inform the Rendering Module ofthe diameter and material of the tubular to simulate the image havingthat diameter and appropriate surface texturing selected from a databaseof materials. Alternatively, the simulated areas of the tubular may beinformed by the high-resolution areas, excluding the localized featureswhich presumably do not extend across the whole tubular. For example,the portions of the imaged area outside of the perforation will informthe rendering module of the radius from the device and surface texture,which may be copied to the nearby simulated areas that are stitched tothe actual imaged areas.

Terms such as “top”, “bottom”, “distal”, “proximate” “downhole”,“uphole”, “below,” “above,” “upper, downstream,” are used herein forsimplicity in describing relative positioning of elements of the tubularor device, as depicted in the drawings or with reference to the surfacedatum. Headings within the detailed descriptions are for readability andnot intended to define the method or device that follows. Although thepresent invention has been described and illustrated with respect topreferred embodiments and preferred uses thereof, it is not to be solimited since modifications and changes can be made therein which arewithin the full, intended scope of the invention as understood by thoseskilled in the art.

1. A method of imaging a localized features in a tubular of an oilwellcomprising deploying and logging an imaging device longitudinallythrough the tubular, which imaging device comprises a) a phased arrayultrasound sensor and b) a camera, longitudinally spaced-apart from theultrasound sensor, and having a higher density of sensor elements thanthe ultrasound sensor; imaging the tubular with the camera to generateoptical images; imaging the tubular with the phased array ultrasoundsensor to generate ultrasound images; wherein both optical images andultrasound images capture localized features in the tubular; andrendering a visualization of the tubular and localized features to auser from the optical and ultrasound images.
 2. The method of claim 1,further comprising automatically detecting the localized features usingthe optical images.
 3. The method of claim 2, further comprising usingthe ultrasound images to combine with or confirm the localized featuresdetected in the optical images.
 4. The method of claim 2, wherein theultrasound sensor provides increased confidence of the detectedlocalized features and camera provides a higher resolution image.
 5. Themethod of claim 2, further comprising processing the optical images orultrasound images to define candidate areas having candidate localizedfeatures then automatically detecting localized features in the definedcandidate areas.
 6. The method of claim 1, wherein the localizedfeatures are at least one of: perforations, ports, holes, corrosion,pits, cracks, connections, wash-outs, or cable clamps.
 7. The method ofclaim 1, wherein rendering comprises overlapping the higher resolutionoptical images and lower resolution ultrasound images at the samelocations to register the lower resolution ultrasound images.
 8. Themethod of claim 1, wherein the step of rendering further comprisesmodifying the optical images to conform with nearby ultrasound images.9. The method of claim 1, further comprising using autocorrelation ofmicro features of the tubular in the optical images or ultrasound imagesfor registration.
 10. The method of claim 1, wherein the step ofrendering creates a 2D or 3D geometric model representing the tubularand localized features in spatial coordinates.
 11. The method of claim1, wherein some parts of the tubular are imaged in high resolution usingthe camera and some parts in low resolution using the ultrasound sensor.12. The method of claim 1, further comprising image processing thecaptured localized features in the optical images or ultrasound imagesto extract a size of the localized feature.
 13. The method of claim 1,further comprising selecting a feature type and using detectionalgorithms on the optical images or ultrasound images to determine amatching value greater than a threshold value to identify candidateareas of the image that contain that feature type.
 14. The method ofclaim 13, wherein the detection algorithm is one or more of:autocorrelation, circle find, Convolutional Neural Net, Region Proposal,template matching, or computer vision.
 15. The method of claim 1,wherein the images are processed by a remote computer after logging. 16.A system for imaging localized features in a tubular in an oilwellcomprising: an elongate imaging device deployable in and moveablethrough the tubular; a phased array ultrasound sensor of the imagingdevice; a camera of the imaging device, longitudinally spaced-apart fromthe phased array ultrasound sensor and having higher density of sensorelements than the ultrasound sensor; one or more memory units forstoring sensor data; and a processor arranged to: i) operate the camerato image the tubular to generate optical images; ii) operate the phasedarray ultrasound sensor to image the tubular to generate ultrasoundimages; and iii) store the images in the memory, wherein both opticalimages and ultrasound images capture localized features in the tubular;and a computer remote from the imaging device and arranged to render avisualization of the tubular and localized features to a user from theoptical and ultrasound images.
 17. The system of claim 16, wherein thecomputer is further arranged to automatically identify the localizedfeatures using the optical images.
 18. The system of claim 17, whereinthe computer is further arranged to use the ultrasound image to combinewith or confirm the localized features identified in the optical image.19. The system of claim 17, wherein the ultrasound sensor providesincreased confidence of the identified localized features and the cameraprovides a higher resolution image of the localized features.
 20. Thesystem of claim 16, wherein the localized features are at least one of:perforations, ports, holes, corrosion, pits, cracks, connections,wash-outs, or cable clamps.
 21. The system of claim 16, whereinrendering comprises overlapping the higher resolution optical images andlower resolution ultrasound images at the same locations to register thelower resolution ultrasound images.
 22. The system of claim 16, whereinthe step of rendering further comprises modifying the optical images toconform with nearby ultrasound images.
 23. The system of claim 16,further comprising using autocorrelation of micro features in theoptical images or ultrasound images for registration.
 24. The system ofclaim 16, wherein the computer is further arranged to render a 2D or 3Dgeometric model representing the localized features.
 25. The system ofclaim 16, wherein some parts of the tubular are imaged in highresolution using the camera and some parts in low resolution using theultrasound sensor.
 26. The system of claim 16, wherein the computer isfurther arranged to image process the captured localized features in theoptical images or ultrasound images to extract a size of the localizedfeature.
 27. The system of claim 16, wherein the computer is furtherarranged to process the optical images or ultrasound images to definecandidate areas having candidate localized features then automaticallydetecting localized features in the defined candidate areas.
 28. Thesystem of claim 27, wherein said detecting uses one or more of:autocorrelation, circle find, Convolutional Neural Net, Region Proposal,template matching, or computer vision.
 29. The system of claim 16,wherein the camera comprises four separate radial-facing cameras, eachcapturing slightly overlapping sectors of the tubular to capture a 360°optical image.
 30. The system of claim 16, wherein the phased arrayultrasound sensor is an array of piezoelectric elements distributedradially around the imaging device.